How do I install the Exa Research Paper Search skill?

Run npx skillmds@latest add codealive-ai/exa-research-paper-search in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Exa Research Paper Search safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Exa Research Paper Search?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Exa Research Paper Search free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Exa Research Paper Search?

CodeAlive-AI (@codealive-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Exa Research Paper Search by codealive-ai

Name: Exa Research Paper Search
Author: CodeAlive-AI

Exa Research Paper Search

Find academic papers with Exa — by topic, author, recency, or as surveys/reviews. Use for literature reviews, finding seminal or state-of-the-art papers, tracking recent preprints (arXiv), or building a reading list. Runs a local script against the Exa API; no MCP server required.

CodeAlive-AI 90923af 2 files · 3.9 KB Updated Sep 17, 2026

File contents

Research Paper Search (Exa)

Find academic papers and preprints via Exa's research-paper index (arXiv and beyond). Calls the Exa REST API through a local script; no MCP server needed, only an EXA_API_KEY.

Setup (once)

export EXA_API_KEY=your-key            # or EXA_API_KEY=... in a .env at the repo root

Get a key at https://dashboard.exa.ai/api-keys. Shared details: exa-native-base.

Run it

python scripts/research_paper_search.py "<topic / method>" [-n N] [--json]

Examples:

python scripts/research_paper_search.py "sparse attention mechanisms for long context transformers" -n 12
python scripts/research_paper_search.py "diffusion models comprehensive survey review" -n 10
python scripts/research_paper_search.py "Geoffrey Hinton forward-forward algorithm" -n 5

Defaults to category=research paper.

Query patterns

# By topic
python scripts/research_paper_search.py "category:research paper retrieval augmented generation robustness" -n 12

# Survey / review papers (best entry point into a field)
python scripts/research_paper_search.py "category:research paper <topic> comprehensive survey review" -n 10

# By author
python scripts/research_paper_search.py "category:research paper <author name> <topic>" -n 5

# By recency — encode the year(s) in the query (don't rely on date filters alone)
python scripts/research_paper_search.py "category:research paper large language model agents 2025 2026" -n 15

To find seminal papers: search for survey/review papers first, then deep-read them to extract the foundational references they cite.

Token isolation (for a literature review)

Decompose into sub-topics and dispatch a subagent per branch (e.g. architectures, training, evaluation, limitations). Each runs 3-5 paper searches and returns a compact table (title · authors · year · venue/arXiv id · one-line contribution). Merge, dedupe by title/arXiv id, then synthesize.

Override categories with `-c`

research paper (default) · pdf (when the paper is a standalone PDF) · news (coverage of a result). For code accompanying a paper, use exa-code-context.

After you get results

Deep-read abstracts/sections: python ../exa-native-base/scripts/exa.py contents <arxiv-url> --text.
For a narrative review, see references/synthesis.md in exa-native-base — organize by theme, cite every claim, surface disagreements.
Deliver a table (title · authors · year · link · contribution) or a themed synthesis with citations.

---name: exa-research-paper-searchdescription: Find academic papers with Exa — by topic, author, recency, or as surveys/reviews. Use for literature reviews, finding seminal or state-of-the-art papers, tracking recent preprints (arXiv), or building a reading list. Runs a local script against the Exa API; no MCP server required.license: MIT---# Research Paper Search (Exa)Find academic papers and preprints via Exa's research-paper index (arXiv and beyond). Calls the Exa REST API through a local script; **no MCP server needed**, only an `EXA_API_KEY`.## Setup (once)```bashexport EXA_API_KEY=your-key # or EXA_API_KEY=... in a .env at the repo root```Get a key at https://dashboard.exa.ai/api-keys. Shared details: [`exa-native-base`](../exa-native-base/SKILL.md).## Run it```bashpython scripts/research_paper_search.py "<topic / method>" [-n N] [--json]```Examples:```bashpython scripts/research_paper_search.py "sparse attention mechanisms for long context transformers" -n 12python scripts/research_paper_search.py "diffusion models comprehensive survey review" -n 10python scripts/research_paper_search.py "Geoffrey Hinton forward-forward algorithm" -n 5```Defaults to `category=research paper`.## Query patterns```bash# By topicpython scripts/research_paper_search.py "category:research paper retrieval augmented generation robustness" -n 12# Survey / review papers (best entry point into a field)python scripts/research_paper_search.py "category:research paper <topic> comprehensive survey review" -n 10# By authorpython scripts/research_paper_search.py "category:research paper <author name> <topic>" -n 5# By recency — encode the year(s) in the query (don't rely on date filters alone)python scripts/research_paper_search.py "category:research paper large language model agents 2025 2026" -n 15```**To find seminal papers:** search for survey/review papers first, then deep-read them to extract the foundational references they cite.## Token isolation (for a literature review)Decompose into sub-topics and dispatch a subagent per branch (e.g. architectures, training, evaluation, limitations). Each runs 3-5 paper searches and returns a compact table (title · authors · year · venue/arXiv id · one-line contribution). Merge, dedupe by title/arXiv id, then synthesize.## Override categories with `-c``research paper` (default) · `pdf` (when the paper is a standalone PDF) · `news` (coverage of a result). For code accompanying a paper, use `exa-code-context`.## After you get results- Deep-read abstracts/sections: `python ../exa-native-base/scripts/exa.py contents <arxiv-url> --text`.- For a narrative review, see `references/synthesis.md` in `exa-native-base` — organize by theme, cite every claim, surface disagreements.- Deliver a table (title · authors · year · link · contribution) or a themed synthesis with citations.

Frequently asked questions